Project Summary/Abstract Although expanded genome-wide association studies (GWAS) have been continuously conducted in breast cancer, only a small fraction of risk alleles has been discovered, and a large proportion of breast cancer genetic variants remains unidentified. Moreover, the biological mechanisms underlying breast cancer are not fully understood. A powerful way to increase our knowledge about the genetic architecture and the biological mechanisms of breast cancer is to explicitly study the genetic determinants of its strong, reliable risk factors. While breast mammogram remains as the cornerstone of early detection of breast cancer, recent studies have found that breast parenchymal texture pattern is an independent yet important risk factor, increasing breast cancer risk by two- to five-folds, however, little is known on its genetic basis. We here propose to conduct a highly cost-efficient GWAS of breast textural features, through leveraging several existing high-quality resources, to understand the genetic structures of breast textures, as well as the shared genetics between breast textures and breast cancer. We will utilize genome-wide genotype data in a total of 7,102 women of European ancestry within the Nurses' Health Studies (NHSI, NHSII), and the Mayo Mammography Health Study (MMHS), who also provided mammograms. As outcomes, we will use seven computer-automated measures of breast textural features, that have been uniformly derived from the collected mammograms. We will conduct study-specific GWAS and combine results through meta-analysis to maximize statistical power. We will also estimate the SNP-heritability of breast textural features using SNPs across the whole genome. Furthermore, we will test if any identified SNPs are also associated with breast cancer risk, through collaboration with the Breast Cancer Association Consortium which recently conducted a breast cancer GWAS comprising a total of 123,000 breast cancer cases and 106,000 controls. We will also investigate whether any breast cancer associations differ by hormone receptor status. Our proposal describes the first GWAS of breast parenchymal textural features, a well-established risk factor for breast cancer. By capitalizing on the well- developed infrastructure for genetic research within NHS, NHSII and MMHS with direct access to GWAS data for more than 7,100 women, we can complete the grant aims in a highly cost-efficient manner. The ultimate objective of this work is to identify genetic predictors of breast textures that could provide insights into mechanistic developmental processes that affect breast cancer risk. We expect that such knowledge will greatly facilitate the early detection of women at high risk as well as provide a platform for development of preventive and treatment strategies for breast cancer.